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<a href="#nested-classes">类</a> &#124;
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<div class="title">pcl::rec_3d_framework::GlobalNNCRHRecognizer&lt; Distance, PointInT, FeatureT &gt; 模板类 参考</div>  </div>
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<p>Nearest neighbor search based classification of PCL point type features. FLANN is used to identify a neighborhood, based on which different scoring schemes can be employed to obtain likelihood values for a specified list of classes. Available features: ESF, VFH, CVFH  
 <a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="global__nn__recognizer__crh_8h_source.html">global_nn_recognizer_crh.h</a>&gt;</code></p>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="nested-classes"></a>
类</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_1_1flann__model.html">flann_model</a></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_1_1index__score.html">index_score</a></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_1_1sort_index_scores.html">sortIndexScores</a></td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:a0c9821ab9ceb889b5645edaa0b9ebc61"><td class="memItemLeft" align="right" valign="top"><a id="a0c9821ab9ceb889b5645edaa0b9ebc61"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><b>setNoise</b> (float n)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setDOCRH</b> (bool b)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setNN</b> (int nn)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setICPIterations</b> (int it)</td></tr>
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<tr class="memitem:ab025e8f0c59d072c65bdf61f9296d9db"><td class="memItemLeft" align="right" valign="top"><a id="ab025e8f0c59d072c65bdf61f9296d9db"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#ab025e8f0c59d072c65bdf61f9296d9db">initialize</a> (bool force_retrain=false)</td></tr>
<tr class="memdesc:ab025e8f0c59d072c65bdf61f9296d9db"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initializes the FLANN structure from the provided source <br /></td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#acfe25d09a89edcf60ac8f31d16607d7d">setDataSource</a> (typename boost::shared_ptr&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_source.html">Source</a>&lt; PointInT &gt; &gt; &amp;source)</td></tr>
<tr class="memdesc:acfe25d09a89edcf60ac8f31d16607d7d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the model data source_ <br /></td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#aca7923e06c6383933931fd7fc923eed4">setFeatureEstimator</a> (typename boost::shared_ptr&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_c_r_h_estimation.html">CRHEstimation</a>&lt; PointInT, FeatureT &gt; &gt; &amp;feat)</td></tr>
<tr class="memdesc:aca7923e06c6383933931fd7fc923eed4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the model data source_ <br /></td></tr>
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<tr class="memitem:a8808672ce98b2a4696d45f8b518350af"><td class="memItemLeft" align="right" valign="top"><a id="a8808672ce98b2a4696d45f8b518350af"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a8808672ce98b2a4696d45f8b518350af">setHVAlgorithm</a> (typename boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_hypothesis_verification.html">HypothesisVerification</a>&lt; PointInT, PointInT &gt; &gt; &amp;alg)</td></tr>
<tr class="memdesc:a8808672ce98b2a4696d45f8b518350af"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the HV algorithm <br /></td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setIndices</b> (std::vector&lt; int &gt; &amp;indices)</td></tr>
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<tr class="memitem:a0bc70540ad5e97cf1190c89d193c3f42"><td class="memItemLeft" align="right" valign="top"><a id="a0bc70540ad5e97cf1190c89d193c3f42"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a0bc70540ad5e97cf1190c89d193c3f42">setInputCloud</a> (const PointInTPtr &amp;cloud)</td></tr>
<tr class="memdesc:a0bc70540ad5e97cf1190c89d193c3f42"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the input cloud to be classified <br /></td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setDescriptorName</b> (std::string &amp;name)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setTrainingDir</b> (std::string &amp;dir)</td></tr>
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<tr class="memitem:a66bbe0bd8a8d63b6d5ce040344ff6c89"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a66bbe0bd8a8d63b6d5ce040344ff6c89">recognize</a> ()</td></tr>
<tr class="memdesc:a66bbe0bd8a8d63b6d5ce040344ff6c89"><td class="mdescLeft">&#160;</td><td class="mdescRight">Performs recognition on the input cloud  <a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a66bbe0bd8a8d63b6d5ce040344ff6c89">更多...</a><br /></td></tr>
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<tr class="memitem:a46f7e9ebb34935ccbafe5ba3d90541b0"><td class="memItemLeft" align="right" valign="top"><a id="a46f7e9ebb34935ccbafe5ba3d90541b0"></a>
boost::shared_ptr&lt; std::vector&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>getModels</b> ()</td></tr>
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boost::shared_ptr&lt; std::vector&lt; Eigen::Matrix4f, Eigen::aligned_allocator&lt; Eigen::Matrix4f &gt; &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>getTransforms</b> ()</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setUseCache</b> (bool u)</td></tr>
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Public 属性</h2></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><b>do_CRH_</b></td></tr>
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Protected 类型</h2></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointInTPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt;::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPointInTPtr</b></td></tr>
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typedef Distance&lt; float &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>DistT</b></td></tr>
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typedef <a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">Model</a>&lt; PointInT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ModelT</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_histogram.html">pcl::Histogram</a>&lt; 90 &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>CRHPointCloud</b></td></tr>
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Protected 成员函数</h2></td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>loadFeaturesAndCreateFLANN</b> ()</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>convertToFLANN</b> (const std::vector&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_1_1flann__model.html">flann_model</a> &gt; &amp;models, <a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; float &gt; &amp;data)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>nearestKSearch</b> (<a class="el" href="classflann_1_1_index.html">flann::Index</a>&lt; DistT &gt; *index, const <a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_1_1flann__model.html">flann_model</a> &amp;model, int k, <a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; int &gt; &amp;indices, <a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; float &gt; &amp;distances)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>getPose</b> (<a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &amp;model, int view_id, Eigen::Matrix4f &amp;pose_matrix)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>getCRH</b> (<a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &amp;model, int view_id, int d_id, CRHPointCloud::Ptr &amp;hist)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>getCentroid</b> (<a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &amp;model, int view_id, int d_id, Eigen::Vector3f &amp;centroid)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>getView</b> (<a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &amp;model, int view_id, PointInTPtr &amp;view)</td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a>
Protected 属性</h2></td></tr>
<tr class="memitem:ab111c507f9621d64ed4295920098c220"><td class="memItemLeft" align="right" valign="top"><a id="ab111c507f9621d64ed4295920098c220"></a>
struct <a class="el" href="structpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_1_1sort_index_scores.html">pcl::rec_3d_framework::GlobalNNCRHRecognizer::sortIndexScores</a>&#160;</td><td class="memItemRight" valign="bottom"><b>sortIndexScoresOp</b></td></tr>
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<tr class="memitem:ae6e4a190cb4d6acd614b2cb242f2762a"><td class="memItemLeft" align="right" valign="top"><a id="ae6e4a190cb4d6acd614b2cb242f2762a"></a>
std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#ae6e4a190cb4d6acd614b2cb242f2762a">training_dir_</a></td></tr>
<tr class="memdesc:ae6e4a190cb4d6acd614b2cb242f2762a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Directory where the trained structure will be saved <br /></td></tr>
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PointInTPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a6d7359c320f452203b7a536575659b08">input_</a></td></tr>
<tr class="memdesc:a6d7359c320f452203b7a536575659b08"><td class="mdescLeft">&#160;</td><td class="mdescRight">Point cloud to be classified <br /></td></tr>
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boost::shared_ptr&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_source.html">pcl::rec_3d_framework::Source</a>&lt; PointInT &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a17fbbeccb1db895396c4598d99269d2d">source_</a></td></tr>
<tr class="memdesc:a17fbbeccb1db895396c4598d99269d2d"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html" title="Model representation">Model</a> data source <br /></td></tr>
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boost::shared_ptr&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_c_r_h_estimation.html">CRHEstimation</a>&lt; PointInT, FeatureT &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a0f740fe86ba4f5df816a69bf9842686f">crh_estimator_</a></td></tr>
<tr class="memdesc:a0f740fe86ba4f5df816a69bf9842686f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes a feature <br /></td></tr>
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boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_hypothesis_verification.html">HypothesisVerification</a>&lt; PointInT, PointInT &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#aebef6788150702505c46004f28550e34">hv_algorithm_</a></td></tr>
<tr class="memdesc:aebef6788150702505c46004f28550e34"><td class="mdescLeft">&#160;</td><td class="mdescRight">Hypotheses verification algorithm <br /></td></tr>
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<tr class="memitem:ab7dd20f705c7496e40b73e8b598a739d"><td class="memItemLeft" align="right" valign="top"><a id="ab7dd20f705c7496e40b73e8b598a739d"></a>
std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#ab7dd20f705c7496e40b73e8b598a739d">descr_name_</a></td></tr>
<tr class="memdesc:ab7dd20f705c7496e40b73e8b598a739d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Descriptor name <br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><b>ICP_iterations_</b></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><b>noisify_</b></td></tr>
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<tr class="memitem:a44c2a904ea6a1854f70b54347cd4ff54"><td class="memItemLeft" align="right" valign="top"><a id="a44c2a904ea6a1854f70b54347cd4ff54"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><b>noise_</b></td></tr>
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<tr class="memitem:a6e5c145de5092c7474b5f89c514f5df5"><td class="memItemLeft" align="right" valign="top"><a id="a6e5c145de5092c7474b5f89c514f5df5"></a>
<a class="el" href="classflann_1_1_matrix.html">flann::Matrix</a>&lt; float &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>flann_data_</b></td></tr>
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<tr class="memitem:a5acead156a2d2ee2a079f49b4bccd0fd"><td class="memItemLeft" align="right" valign="top"><a id="a5acead156a2d2ee2a079f49b4bccd0fd"></a>
<a class="el" href="classflann_1_1_index.html">flann::Index</a>&lt; DistT &gt; *&#160;</td><td class="memItemRight" valign="bottom"><b>flann_index_</b></td></tr>
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std::vector&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_1_1flann__model.html">flann_model</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>flann_models_</b></td></tr>
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<tr class="memitem:ab0565092a1f34b1dd897cc2bf7c09657"><td class="memItemLeft" align="right" valign="top"><a id="ab0565092a1f34b1dd897cc2bf7c09657"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><b>use_cache_</b></td></tr>
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std::map&lt; std::pair&lt; std::string, int &gt;, Eigen::Matrix4f, std::less&lt; std::pair&lt; std::string, int &gt; &gt;, Eigen::aligned_allocator&lt; std::pair&lt; std::pair&lt; std::string, int &gt;, Eigen::Matrix4f &gt; &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>poses_cache_</b></td></tr>
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std::map&lt; std::pair&lt; std::string, int &gt;, Eigen::Vector3f &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>centroids_cache_</b></td></tr>
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<tr class="memitem:af5b2bb9447900b0c5f4e9921a31a710b"><td class="memItemLeft" align="right" valign="top"><a id="af5b2bb9447900b0c5f4e9921a31a710b"></a>
std::vector&lt; int &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>indices_</b></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><b>NN_</b></td></tr>
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boost::shared_ptr&lt; std::vector&lt; <a class="el" href="classpcl_1_1rec__3d__framework_1_1_model.html">ModelT</a> &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>models_</b></td></tr>
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boost::shared_ptr&lt; std::vector&lt; Eigen::Matrix4f, Eigen::aligned_allocator&lt; Eigen::Matrix4f &gt; &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>transforms_</b></td></tr>
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</table>
<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;template&lt; class &gt; class Distance, typename PointInT, typename FeatureT&gt;<br />
class pcl::rec_3d_framework::GlobalNNCRHRecognizer&lt; Distance, PointInT, FeatureT &gt;</h3>

<p>Nearest neighbor search based classification of PCL point type features. FLANN is used to identify a neighborhood, based on which different scoring schemes can be employed to obtain likelihood values for a specified list of classes. Available features: ESF, VFH, CVFH </p>
<dl class="section author"><dt>作者</dt><dd>Aitor Aldoma </dd></dl>
</div><h2 class="groupheader">成员函数说明</h2>
<a id="a66bbe0bd8a8d63b6d5ce040344ff6c89"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a66bbe0bd8a8d63b6d5ce040344ff6c89">&#9670;&nbsp;</a></span>recognize()</h2>

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<div class="memproto">
<div class="memtemplate">
template&lt;template&lt; class &gt; class Distance, typename PointInT , typename FeatureT &gt; </div>
      <table class="memname">
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          <td class="memname">void <a class="el" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html">pcl::rec_3d_framework::GlobalNNCRHRecognizer</a>&lt; Distance, PointInT, FeatureT &gt;::recognize</td>
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<p>Performs recognition on the input cloud </p>
<p>POSE REFINEMENT</p>
<p>HYPOTHESES VERIFICATION</p>
<div class="fragment"><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  {</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160; </div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    models_.reset (<span class="keyword">new</span> std::vector&lt;ModelT&gt;);</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    transforms_.reset (<span class="keyword">new</span> std::vector&lt;Eigen::Matrix4f, Eigen::aligned_allocator&lt;Eigen::Matrix4f&gt; &gt;);</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160; </div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    PointInTPtr processed (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;    PointInTPtr in (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160; </div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;    std::vector&lt;pcl::PointCloud&lt;FeatureT&gt;, Eigen::aligned_allocator&lt;pcl::PointCloud&lt;FeatureT&gt; &gt; &gt; signatures;</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    std::vector &lt; Eigen::Vector3f, Eigen::aligned_allocator&lt;Eigen::Vector3f&gt; &gt; centroids;</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160; </div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    <span class="keywordflow">if</span> (indices_.size ())</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;      <a class="code" href="group__common.html#gaa65b1c8d782e7b776ae682679d2d948f">pcl::copyPointCloud</a> (*<a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a6d7359c320f452203b7a536575659b08">input_</a>, indices_, *in);</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <span class="keywordflow">else</span></div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;      in = <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a6d7359c320f452203b7a536575659b08">input_</a>;</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160; </div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    {</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;      <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;Estimate feature&quot;</span>);</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;      <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a0f740fe86ba4f5df816a69bf9842686f">crh_estimator_</a>-&gt;estimate (in, processed, signatures, centroids);</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    }</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160; </div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    std::vector&lt;CRHPointCloud::Ptr&gt; crh_histograms;</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a0f740fe86ba4f5df816a69bf9842686f">crh_estimator_</a>-&gt;getCRHHistograms (crh_histograms);</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160; </div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    std::vector&lt;index_score&gt; indices_scores;</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    <span class="keywordflow">if</span> (signatures.size () &gt; 0)</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;    {</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160; </div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;      {</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;        <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t_matching (<span class="stringliteral">&quot;Matching and roll...&quot;</span>);</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> idx = 0; idx &lt; signatures.size (); idx++)</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;        {</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160; </div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;          <span class="keywordtype">float</span>* hist = signatures[idx].points[0].histogram;</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;          <span class="keywordtype">int</span> size_feat = <span class="keyword">sizeof</span>(signatures[idx].points[0].histogram) / <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>);</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;          std::vector&lt;float&gt; std_hist (hist, hist + size_feat);</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;          ModelT empty;</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160; </div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;          flann_model histogram;</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;          histogram.descr = std_hist;</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160; </div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;          <a class="code" href="classflann_1_1_matrix.html">flann::Matrix&lt;int&gt;</a> indices;</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;          <a class="code" href="classflann_1_1_matrix.html">flann::Matrix&lt;float&gt;</a> distances;</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;          nearestKSearch (flann_index_, histogram, NN_, indices, distances);</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160; </div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;          <span class="comment">//gather NN-search results</span></div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;          <span class="keywordtype">double</span> score = 0;</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NN_; ++i)</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;          {</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;            score = distances[0][i];</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;            index_score is;</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;            is.idx_models_ = indices[0][i];</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;            is.idx_input_ = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (idx);</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;            is.score_ = score;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;            indices_scores.push_back (is);</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;          }</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;        }</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160; </div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;        std::sort (indices_scores.begin (), indices_scores.end (), sortIndexScoresOp);</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160; </div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;        <span class="keywordtype">int</span> num_n = std::min (NN_, <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (indices_scores.size ()));</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160; </div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;        <span class="comment">/*</span></div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;<span class="comment">         * Filter some hypothesis regarding to their distance to the first neighbour</span></div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;<span class="comment">         */</span></div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160; </div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;        <span class="comment">/*std::vector&lt;index_score&gt; indices_scores_filtered;</span></div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;<span class="comment">        indices_scores_filtered.resize (num_n);</span></div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;<span class="comment">        indices_scores_filtered[0] = indices_scores[0];</span></div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;<span class="comment">        float best_score = indices_scores[0].score_;</span></div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;<span class="comment">        int kept = 1;</span></div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;<span class="comment">        for (int i = 1; i &lt; num_n; ++i)</span></div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;<span class="comment">        {</span></div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;<span class="comment">          std::cout &lt;&lt; best_score &lt;&lt; indices_scores[i].score_ &lt;&lt; (best_score / indices_scores[i].score_) &lt;&lt; std::endl;</span></div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;<span class="comment">          if ((best_score / indices_scores[i].score_) &gt; 0.75)</span></div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;<span class="comment">          {</span></div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;<span class="comment">            indices_scores_filtered[i] = indices_scores[i];</span></div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;<span class="comment">            kept++;</span></div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;<span class="comment">          }</span></div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;<span class="comment">          //best_score = indices_scores[i].score_;</span></div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;<span class="comment">        }</span></div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;<span class="comment">        indices_scores_filtered.resize (kept);</span></div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;<span class="comment">        std::cout &lt;&lt; indices_scores_filtered.size () &lt;&lt; &quot; § &quot; &lt;&lt; num_n &lt;&lt; std::endl;</span></div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;<span class="comment">        indices_scores = indices_scores_filtered;</span></div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;<span class="comment">        num_n = indices_scores.size ();*/</span></div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160; </div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;        <span class="keywordflow">if</span> (do_CRH_)</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;        {</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;          <span class="comment">/*</span></div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;<span class="comment">           * Once we have the models, we need to find a 6DOF pose using the roll histogram</span></div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;<span class="comment">           * pass to pcl_recognition::CRHAlignment both views, centroids and CRH</span></div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;<span class="comment">           */</span></div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160; </div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;          <a class="code" href="classpcl_1_1_c_r_h_alignment.html">pcl::CRHAlignment&lt;PointInT, 90&gt;</a> crha;</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160; </div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; num_n; ++i)</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;          {</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;            ModelT m = flann_models_[indices_scores[i].idx_models_].model;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;            <span class="keywordtype">int</span> view_id = flann_models_[indices_scores[i].idx_models_].view_id;</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;            <span class="keywordtype">int</span> desc_id = flann_models_[indices_scores[i].idx_models_].descriptor_id;</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160; </div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;            std::cout &lt;&lt; m.id_ &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; view_id &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; desc_id &lt;&lt; std::endl;</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160; </div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;            <span class="comment">//get crhs</span></div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;            CRHPointCloud::Ptr input_crh = crh_histograms[indices_scores[i].idx_input_];</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;            CRHPointCloud::Ptr view_crh;</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;            getCRH (m, view_id, desc_id, view_crh);</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160; </div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;            <span class="comment">//get centroids</span></div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;            Eigen::Vector3f input_centroid = centroids[indices_scores[i].idx_input_];</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;            Eigen::Vector3f view_centroid;</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;            getCentroid (m, view_id, desc_id, view_centroid);</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160; </div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;            <span class="comment">//crha.setModelAndInputView (view, processed);</span></div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;            crha.<a class="code" href="classpcl_1_1_c_r_h_alignment.html#a3035ec22c3d01de1b2bf7a14c78213ab">setInputAndTargetCentroids</a> (view_centroid, input_centroid);</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;            crha.<a class="code" href="classpcl_1_1_c_r_h_alignment.html#a32c40356d56e22d48eccce5e27e436f2">align</a> (*view_crh, *input_crh);</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160; </div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;            Eigen::Matrix4f model_view_pose;</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;            getPose (m, view_id, model_view_pose);</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160; </div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;            std::vector &lt; Eigen::Matrix4f, Eigen::aligned_allocator&lt;Eigen::Matrix4f&gt; &gt; roll_transforms;</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;            crha.<a class="code" href="classpcl_1_1_c_r_h_alignment.html#ad25e7de96ca4c5c55d87dc3bacf804ca">getTransforms</a> (roll_transforms);</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160; </div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;            <span class="comment">//create object hypothesis</span></div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> k = 0; k &lt; roll_transforms.size (); k++)</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;            {</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;              Eigen::Matrix4f final_roll_trans (roll_transforms[k] * model_view_pose);</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;              models_-&gt;push_back (m);</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;              transforms_-&gt;push_back (final_roll_trans);</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;            }</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;          }</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;        }</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;        <span class="keywordflow">else</span></div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;        {</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; num_n; ++i)</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;          {</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;            ModelT m = flann_models_[indices_scores[i].idx_models_].model;</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;            models_-&gt;push_back (m);</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;          }</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;        }</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;      }</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160; </div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;      std::cout &lt;&lt; <span class="stringliteral">&quot;Number of object hypotheses:&quot;</span> &lt;&lt; models_-&gt;size () &lt;&lt; std::endl;</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160; </div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;      <span class="keywordflow">if</span> (ICP_iterations_ &gt; 0)</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;      {</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;        <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;Pose refinement&quot;</span>);</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160; </div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;        <span class="comment">//Prepare scene and model clouds for the pose refinement step</span></div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;        <span class="keywordtype">float</span> VOXEL_SIZE_ICP_ = 0.005f;</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;        PointInTPtr cloud_voxelized_icp (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a> ());</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;        <a class="code" href="classpcl_1_1_voxel_grid.html">pcl::VoxelGrid&lt;PointInT&gt;</a> voxel_grid_icp;</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;        voxel_grid_icp.<a class="code" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a> (processed);</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;        voxel_grid_icp.<a class="code" href="classpcl_1_1_voxel_grid.html#aa5d7831e665977bdce76ed05bd0005cf">setLeafSize</a> (VOXEL_SIZE_ICP_, VOXEL_SIZE_ICP_, VOXEL_SIZE_ICP_);</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;        voxel_grid_icp.<a class="code" href="classpcl_1_1_filter.html#a17115897ca28f6b12950d023958aa641">filter</a> (*cloud_voxelized_icp);</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a17fbbeccb1db895396c4598d99269d2d">source_</a>-&gt;voxelizeAllModels (VOXEL_SIZE_ICP_);</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160; </div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;<span class="preprocessor">#pragma omp parallel for num_threads(omp_get_num_procs())</span></div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; static_cast&lt;int&gt; (models_-&gt;size ()); i++)</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;        {</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160; </div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;          ConstPointInTPtr model_cloud = models_-&gt;at (i).getAssembled (VOXEL_SIZE_ICP_);</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;          PointInTPtr model_aligned (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;          <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*model_cloud, *model_aligned, transforms_-&gt;at (i));</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160; </div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;          <a class="code" href="classpcl_1_1_iterative_closest_point.html">pcl::IterativeClosestPoint&lt;PointInT, PointInT&gt;</a> reg;</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;          reg.<a class="code" href="classpcl_1_1_iterative_closest_point.html#ad5215429e057c8760ac48e9bdb09b12c">setInputSource</a> (model_aligned); <span class="comment">//model</span></div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;          reg.<a class="code" href="classpcl_1_1_iterative_closest_point.html#a8876f743cc31471a975e950e66c179d4">setInputTarget</a> (cloud_voxelized_icp); <span class="comment">//scene</span></div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;          reg.<a class="code" href="classpcl_1_1_registration.html#a3844d186f7a99d15464368e0f25635ed">setMaximumIterations</a> (ICP_iterations_);</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;          reg.<a class="code" href="classpcl_1_1_registration.html#a65596dcc3cb5d2647857226fb3d999a5">setMaxCorrespondenceDistance</a> (VOXEL_SIZE_ICP_ * 3.f);</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;          reg.<a class="code" href="classpcl_1_1_registration.html#aec74ab878cca8d62fd1be9942685a8c1">setTransformationEpsilon</a> (1e-5);</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160; </div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;          <span class="keyword">typename</span> pcl::PointCloud&lt;PointInT&gt;::Ptr output_ (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a> ());</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;          reg.<a class="code" href="classpcl_1_1_registration.html#a96212303ca16b6d60020824086887c4f">align</a> (*output_);</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160; </div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;          Eigen::Matrix4f icp_trans = reg.<a class="code" href="classpcl_1_1_registration.html#a1e68bd39ac943131dcbf1431f9afe3f3">getFinalTransformation</a> ();</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;          transforms_-&gt;at (i) = icp_trans * transforms_-&gt;at (i);</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;        }</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;      }</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160; </div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;      <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#aebef6788150702505c46004f28550e34">hv_algorithm_</a>)</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;      {</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160; </div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;        <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;HYPOTHESES VERIFICATION&quot;</span>);</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160; </div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;        std::vector&lt;typename pcl::PointCloud&lt;PointInT&gt;::ConstPtr&gt; aligned_models;</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;        aligned_models.resize (models_-&gt;size ());</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160; </div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; models_-&gt;size (); i++)</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;        {</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;          ConstPointInTPtr model_cloud = models_-&gt;at (i).getAssembled (0.005f);</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;          PointInTPtr model_aligned (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;          <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*model_cloud, *model_aligned, transforms_-&gt;at (i));</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;          aligned_models[i] = model_aligned;</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;        }</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160; </div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;        std::vector&lt;bool&gt; mask_hv;</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#aebef6788150702505c46004f28550e34">hv_algorithm_</a>-&gt;setSceneCloud (<a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a6d7359c320f452203b7a536575659b08">input_</a>);</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#aebef6788150702505c46004f28550e34">hv_algorithm_</a>-&gt;addModels (aligned_models, <span class="keyword">true</span>);</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#aebef6788150702505c46004f28550e34">hv_algorithm_</a>-&gt;verify ();</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;        <a class="code" href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#aebef6788150702505c46004f28550e34">hv_algorithm_</a>-&gt;getMask (mask_hv);</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160; </div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;        boost::shared_ptr &lt; std::vector&lt;ModelT&gt; &gt; models_temp;</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;        boost::shared_ptr &lt; std::vector&lt;Eigen::Matrix4f, Eigen::aligned_allocator&lt;Eigen::Matrix4f&gt; &gt; &gt; transforms_temp;</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160; </div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;        models_temp.reset (<span class="keyword">new</span> std::vector&lt;ModelT&gt;);</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;        transforms_temp.reset (<span class="keyword">new</span> std::vector&lt;Eigen::Matrix4f, Eigen::aligned_allocator&lt;Eigen::Matrix4f&gt; &gt;);</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160; </div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; models_-&gt;size (); i++)</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;        {</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;          <span class="keywordflow">if</span> (!mask_hv[i])</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;            <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160; </div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;          models_temp-&gt;push_back (models_-&gt;at (i));</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;          transforms_temp-&gt;push_back (transforms_-&gt;at (i));</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;        }</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160; </div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;        models_ = models_temp;</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;        transforms_ = transforms_temp;</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;      }</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160; </div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;    }</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;  }</div>
<div class="ttc" id="aclassflann_1_1_matrix_html"><div class="ttname"><a href="classflann_1_1_matrix.html">flann::Matrix</a></div><div class="ttdef"><b>Definition:</b> flann_search.h:51</div></div>
<div class="ttc" id="aclasspcl_1_1_c_r_h_alignment_html"><div class="ttname"><a href="classpcl_1_1_c_r_h_alignment.html">pcl::CRHAlignment</a></div><div class="ttdoc">CRHAlignment uses two Camera Roll Histograms (CRH) to find the roll rotation that aligns both views....</div><div class="ttdef"><b>Definition:</b> crh_alignment.h:32</div></div>
<div class="ttc" id="aclasspcl_1_1_c_r_h_alignment_html_a3035ec22c3d01de1b2bf7a14c78213ab"><div class="ttname"><a href="classpcl_1_1_c_r_h_alignment.html#a3035ec22c3d01de1b2bf7a14c78213ab">pcl::CRHAlignment::setInputAndTargetCentroids</a></div><div class="ttdeci">void setInputAndTargetCentroids(Eigen::Vector3f &amp;c1, Eigen::Vector3f &amp;c2)</div><div class="ttdoc">sets model and input centroids</div><div class="ttdef"><b>Definition:</b> crh_alignment.h:136</div></div>
<div class="ttc" id="aclasspcl_1_1_c_r_h_alignment_html_a32c40356d56e22d48eccce5e27e436f2"><div class="ttname"><a href="classpcl_1_1_c_r_h_alignment.html#a32c40356d56e22d48eccce5e27e436f2">pcl::CRHAlignment::align</a></div><div class="ttdeci">void align(pcl::PointCloud&lt; pcl::Histogram&lt; nbins_ &gt; &gt; &amp;input_ftt, pcl::PointCloud&lt; pcl::Histogram&lt; nbins_ &gt; &gt; &amp;target_ftt)</div><div class="ttdoc">Computes the transformation aligning model to input</div><div class="ttdef"><b>Definition:</b> crh_alignment.h:147</div></div>
<div class="ttc" id="aclasspcl_1_1_c_r_h_alignment_html_ad25e7de96ca4c5c55d87dc3bacf804ca"><div class="ttname"><a href="classpcl_1_1_c_r_h_alignment.html#ad25e7de96ca4c5c55d87dc3bacf804ca">pcl::CRHAlignment::getTransforms</a></div><div class="ttdeci">void getTransforms(std::vector&lt; Eigen::Matrix4f, Eigen::aligned_allocator&lt; Eigen::Matrix4f &gt; &gt; &amp;transforms)</div><div class="ttdoc">returns the computed transformations</div><div class="ttdef"><b>Definition:</b> crh_alignment.h:116</div></div>
<div class="ttc" id="aclasspcl_1_1_filter_html_a17115897ca28f6b12950d023958aa641"><div class="ttname"><a href="classpcl_1_1_filter.html#a17115897ca28f6b12950d023958aa641">pcl::Filter::filter</a></div><div class="ttdeci">void filter(PointCloud &amp;output)</div><div class="ttdoc">Calls the filtering method and returns the filtered dataset in output.</div><div class="ttdef"><b>Definition:</b> filter.h:132</div></div>
<div class="ttc" id="aclasspcl_1_1_iterative_closest_point_html"><div class="ttname"><a href="classpcl_1_1_iterative_closest_point.html">pcl::IterativeClosestPoint</a></div><div class="ttdoc">IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm....</div><div class="ttdef"><b>Definition:</b> icp.h:95</div></div>
<div class="ttc" id="aclasspcl_1_1_iterative_closest_point_html_a8876f743cc31471a975e950e66c179d4"><div class="ttname"><a href="classpcl_1_1_iterative_closest_point.html#a8876f743cc31471a975e950e66c179d4">pcl::IterativeClosestPoint::setInputTarget</a></div><div class="ttdeci">virtual void setInputTarget(const PointCloudTargetConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input target (e.g., the point cloud that we want to align to the target)</div><div class="ttdef"><b>Definition:</b> icp.h:212</div></div>
<div class="ttc" id="aclasspcl_1_1_iterative_closest_point_html_ad5215429e057c8760ac48e9bdb09b12c"><div class="ttname"><a href="classpcl_1_1_iterative_closest_point.html#ad5215429e057c8760ac48e9bdb09b12c">pcl::IterativeClosestPoint::setInputSource</a></div><div class="ttdeci">virtual void setInputSource(const PointCloudSourceConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input source (e.g., the point cloud that we want to align to the target)</div><div class="ttdef"><b>Definition:</b> icp.h:177</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_a1952d7101f3942bac3b69ed55c1ca7ea"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">pcl::PCLBase::setInputCloud</a></div><div class="ttdeci">virtual void setInputCloud(const PointCloudConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input dataset</div><div class="ttdef"><b>Definition:</b> pcl_base.hpp:66</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt; PointInT &gt;</a></div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a1e68bd39ac943131dcbf1431f9afe3f3"><div class="ttname"><a href="classpcl_1_1_registration.html#a1e68bd39ac943131dcbf1431f9afe3f3">pcl::Registration::getFinalTransformation</a></div><div class="ttdeci">Matrix4 getFinalTransformation()</div><div class="ttdoc">Get the final transformation matrix estimated by the registration method.</div><div class="ttdef"><b>Definition:</b> registration.h:275</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a3844d186f7a99d15464368e0f25635ed"><div class="ttname"><a href="classpcl_1_1_registration.html#a3844d186f7a99d15464368e0f25635ed">pcl::Registration::setMaximumIterations</a></div><div class="ttdeci">void setMaximumIterations(int nr_iterations)</div><div class="ttdoc">Set the maximum number of iterations the internal optimization should run for.</div><div class="ttdef"><b>Definition:</b> registration.h:285</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a65596dcc3cb5d2647857226fb3d999a5"><div class="ttname"><a href="classpcl_1_1_registration.html#a65596dcc3cb5d2647857226fb3d999a5">pcl::Registration::setMaxCorrespondenceDistance</a></div><div class="ttdeci">void setMaxCorrespondenceDistance(double distance_threshold)</div><div class="ttdoc">Set the maximum distance threshold between two correspondent points in source &lt;-&gt; target....</div><div class="ttdef"><b>Definition:</b> registration.h:321</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a96212303ca16b6d60020824086887c4f"><div class="ttname"><a href="classpcl_1_1_registration.html#a96212303ca16b6d60020824086887c4f">pcl::Registration::align</a></div><div class="ttdeci">void align(PointCloudSource &amp;output)</div><div class="ttdoc">Call the registration algorithm which estimates the transformation and returns the transformed source...</div><div class="ttdef"><b>Definition:</b> registration.hpp:169</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_aec74ab878cca8d62fd1be9942685a8c1"><div class="ttname"><a href="classpcl_1_1_registration.html#aec74ab878cca8d62fd1be9942685a8c1">pcl::Registration::setTransformationEpsilon</a></div><div class="ttdeci">void setTransformationEpsilon(double epsilon)</div><div class="ttdoc">Set the transformation epsilon (maximum allowable difference between two consecutive transformations)...</div><div class="ttdef"><b>Definition:</b> registration.h:336</div></div>
<div class="ttc" id="aclasspcl_1_1_scope_time_html"><div class="ttname"><a href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a></div><div class="ttdoc">Class to measure the time spent in a scope</div><div class="ttdef"><b>Definition:</b> time.h:118</div></div>
<div class="ttc" id="aclasspcl_1_1_voxel_grid_html"><div class="ttname"><a href="classpcl_1_1_voxel_grid.html">pcl::VoxelGrid</a></div><div class="ttdoc">VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data.</div><div class="ttdef"><b>Definition:</b> voxel_grid.h:179</div></div>
<div class="ttc" id="aclasspcl_1_1_voxel_grid_html_aa5d7831e665977bdce76ed05bd0005cf"><div class="ttname"><a href="classpcl_1_1_voxel_grid.html#aa5d7831e665977bdce76ed05bd0005cf">pcl::VoxelGrid::setLeafSize</a></div><div class="ttdeci">void setLeafSize(const Eigen::Vector4f &amp;leaf_size)</div><div class="ttdoc">Set the voxel grid leaf size.</div><div class="ttdef"><b>Definition:</b> voxel_grid.h:223</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_html_a0f740fe86ba4f5df816a69bf9842686f"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a0f740fe86ba4f5df816a69bf9842686f">pcl::rec_3d_framework::GlobalNNCRHRecognizer::crh_estimator_</a></div><div class="ttdeci">boost::shared_ptr&lt; CRHEstimation&lt; PointInT, FeatureT &gt; &gt; crh_estimator_</div><div class="ttdoc">Computes a feature</div><div class="ttdef"><b>Definition:</b> global_nn_recognizer_crh.h:70</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_html_a17fbbeccb1db895396c4598d99269d2d"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a17fbbeccb1db895396c4598d99269d2d">pcl::rec_3d_framework::GlobalNNCRHRecognizer::source_</a></div><div class="ttdeci">boost::shared_ptr&lt; pcl::rec_3d_framework::Source&lt; PointInT &gt; &gt; source_</div><div class="ttdoc">Model data source</div><div class="ttdef"><b>Definition:</b> global_nn_recognizer_crh.h:67</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_html_a6d7359c320f452203b7a536575659b08"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#a6d7359c320f452203b7a536575659b08">pcl::rec_3d_framework::GlobalNNCRHRecognizer::input_</a></div><div class="ttdeci">PointInTPtr input_</div><div class="ttdoc">Point cloud to be classified</div><div class="ttdef"><b>Definition:</b> global_nn_recognizer_crh.h:64</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer_html_aebef6788150702505c46004f28550e34"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_global_n_n_c_r_h_recognizer.html#aebef6788150702505c46004f28550e34">pcl::rec_3d_framework::GlobalNNCRHRecognizer::hv_algorithm_</a></div><div class="ttdeci">boost::shared_ptr&lt; HypothesisVerification&lt; PointInT, PointInT &gt; &gt; hv_algorithm_</div><div class="ttdoc">Hypotheses verification algorithm</div><div class="ttdef"><b>Definition:</b> global_nn_recognizer_crh.h:73</div></div>
<div class="ttc" id="agroup__common_html_ga52d532f7f2b4d7bba78d13701d3a33d8"><div class="ttname"><a href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a></div><div class="ttdeci">void transformPointCloud(const pcl::PointCloud&lt; PointT &gt; &amp;cloud_in, pcl::PointCloud&lt; PointT &gt; &amp;cloud_out, const Eigen::Transform&lt; Scalar, 3, Eigen::Affine &gt; &amp;transform, bool copy_all_fields=true)</div><div class="ttdoc">Apply an affine transform defined by an Eigen Transform</div><div class="ttdef"><b>Definition:</b> transforms.hpp:42</div></div>
<div class="ttc" id="agroup__common_html_gaa65b1c8d782e7b776ae682679d2d948f"><div class="ttname"><a href="group__common.html#gaa65b1c8d782e7b776ae682679d2d948f">pcl::copyPointCloud</a></div><div class="ttdeci">PCL_EXPORTS void copyPointCloud(const pcl::PCLPointCloud2 &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, pcl::PCLPointCloud2 &amp;cloud_out)</div><div class="ttdoc">Extract the indices of a given point cloud as a new point cloud</div></div>
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